Tamara Broderick

Tamara Broderick is an Associate Professor with tenure at MIT, affiliated with the Electrical Engineering and Computer Science (EECS) Department, the Laboratory for Information and Decision Systems (LIDS), and the Institute for Data, Systems, and Society (IDSS). Her research focuses on machine learning and statistics, particularly Bayesian methods, uncertainty quantification, and probabilistic modeling. She completed her PhD at UC Berkeley and has held significant roles in advancing scalable Bayesian inference techniques.

Her work includes developing the Nomon assistive technology for single-switch users, showcased in projects like the Harlem Shake video explaining MCMC methods. She teaches advanced courses such as 6.7830 Bayesian Modeling and Inference in Spring 2025. Broderick advises numerous PhD students and postdocs, mentoring in EECS and related MIT programs. Her contributions span theoretical advancements, practical algorithms, and impactful applications in healthcare and accessibility.